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, machine learning, and statistical methods for time-series forecasting in the electricity sector, including demand, renewable generation, and market prices. Development and evaluation of point and
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Machine Learning group at TDB and SciLifeLab (Associate Professor Prashant Singh), which develops methods and software for simulation-based inference, generative models and robust machine learning, together
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19 Sep 2026 Job Information Organisation/Company Radboud University Research Field Computer science » Modelling tools Computer science » Programming Engineering » Computer engineering Engineering
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will join a research group working on longitudinal models of multiple chronic diseases across the life course. The postdoctoral researcher will contribute to building and evaluating machine learning
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environment. 4) Development of machine learning and deep learning models for forecasting reduced visibility, low cloud ceilings, and adverse weather conditions impacting air operations. 5) Implementation
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Technische Hochschule Brandenburg | Brandenburg an der Havel, Brandenburg | Germany | about 2 hours ago
of these approaches quickly, in a data-based and reliable manner. Your main tasks include: Method development: you compare and decide on methods of Machine Learning (ML) and Artificial Intelligence (AI), such as
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with health/real grid data or machine learning is beneficial but not mandatory. We Offer One year funded of 3-year PhD position (SIF Doctoral Student Grant). Access to high-performance computing
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 14 hours ago
. Examples include: determination of high-resolution shape models using shape-from-shading or novel machine-learning methods; studies of high-resolution shape models for geophysical and geological studies
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an advantage: plasma surface functionalization; electrode/electrolyte interfaces; battery degradation modelling; microstructure-resolved modelling; tomography or image-based electrode modelling; machine learning
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, organization, and function; models of perception, cognition, learning, and behavior; and statistical and machine-learning approaches for understanding neural data and brain function. We are particularly